RESUMEN
Caspase recruitment domain family member 14 (CARD14) and its variants are associated with both atopic dermatitis (AD) and psoriasis, but their mechanistic impact on skin barrier homeostasis is largely unknown. CARD14 is known to signal via NF-κB; however, CARD14-NF-κB signaling does not fully explain the heterogeneity of CARD14-driven disease. Here, we describe a direct interaction between CARD14 and MYC and show that CARD14 signals through MYC in keratinocytes to coordinate skin barrier homeostasis. CARD14 directly binds MYC and influences barrier formation in an MYC-dependent fashion, and this mechanism is undermined by disease-associated CARD14 variants. These studies establish a paradigm that CARD14 activation regulates skin barrier function by two distinct mechanisms, including activating NF-κB to bolster the antimicrobial (chemical) barrier and stimulating MYC to bolster the physical barrier. Finally, we show that CARD14-dependent MYC signaling occurs in other epithelia, expanding the impact of our findings beyond the skin.
Asunto(s)
Proteínas Adaptadoras de Señalización CARD , Epidermis , Homeostasis , Queratinocitos , FN-kappa B , Proteínas Proto-Oncogénicas c-myc , Humanos , Proteínas Adaptadoras de Señalización CARD/metabolismo , Proteínas Adaptadoras de Señalización CARD/genética , Proteínas Proto-Oncogénicas c-myc/metabolismo , Proteínas Proto-Oncogénicas c-myc/genética , Epidermis/metabolismo , Queratinocitos/metabolismo , FN-kappa B/metabolismo , Transducción de Señal , Dermatitis Atópica/metabolismo , Dermatitis Atópica/patología , Dermatitis Atópica/genética , Guanilato Ciclasa/metabolismo , Guanilato Ciclasa/genética , Epitelio/metabolismo , Unión Proteica , Psoriasis/metabolismo , Psoriasis/genética , Psoriasis/patología , Proteínas de la MembranaRESUMEN
Background: Stuttering priapism is recurrent, self-limited episodes of sustained penile erection and is common in patients with sickle cell disease (SCD). Prevention of stuttering priapism is important to avoid progression to episodes of ischemic priapism which can cause erectile dysfunction. Priapism has been shown to be associated with increased nocturnal hypoxemia in patients with SCD. Case Description: A 43-year-old male with nocturnal episodes of stuttering priapism that was refractory to treatment with multiple medications was found to have obstructive sleep apnea (OSA). Following treatment of this condition with a continuous positive airway pressure (CPAP), the patient had immediate symptom relief and has had three months without an episode of priapism. Conclusions: OSA should be considered as an underlying cause of nocturnal stuttering priapism in patients with SCD, particularly in patients who present with stuttering priapism later in life or patients who present strictly with nocturnal episodes. Appropriate management of OSA can significantly decrease the incidence of stuttering priapism in patients with SCD.
RESUMEN
The analysis of fish behavior in response to odor stimulation is a crucial component of the general study of cross-modal sensory integration in vertebrates. In zebrafish, the centrifugal pathway runs between the olfactory bulb and the neural retina, originating at the terminalis neuron in the olfactory bulb. Any changes in the ambient odor of a fish's environment warrant a change in visual sensitivity and can trigger mating-like behavior in males due to increased GnRH signaling in the terminalis neuron. Behavioral experiments to study this phenomenon are commonly conducted in a controlled environment where a video of the fish is recorded over time before and after the application of chemicals to the water. Given the subtleties of behavioral change, trained biologists are currently required to annotate such videos as part of a study. This process of manually analyzing the videos is time-consuming, requires multiple experts to avoid human error/bias and cannot be easily crowdsourced on the Internet. Machine learning algorithms from computer vision, on the other hand, have proven to be effective for video annotation tasks because they are fast, accurate, and, if designed properly, can be less biased than humans. In this work, we propose to automate the entire process of analyzing videos of behavior changes in zebrafish by using tools from computer vision, relying on minimal expert supervision. The overall objective of this work is to create a generalized tool to predict animal behaviors from videos using state-of-the-art deep learning models, with the dual goal of advancing understanding in biology and engineering a more robust and powerful artificial information processing system for biologists.